Perceptron is a machine learning technique that can be used to predict market prices. It is a useful tool for traders and investors striving to get a price forecast. more...
Displaying the data in different domains can reveal interesting characteristics about the series that may not be apparent when conducting analysis exclusively in the time domain. In this article we will discuss some of the useful perspectives to be gained by analyzing time series in the frequency domain using the discrete fourier transform (dft). more...
In our previous article, on category theory, we uncovered the key concepts of multi-sets, relative sets, and indexed sets and explored their significance in algorithmic trading. Now, in this follow-up, we introduce the concept of monoids. Monoids form an essential foundation in mathematics and computer science, providing a structured approach to modeling operations on sets of elements. more...
Normalization of inputs is an important step in preparing data for training neural networks. This process allows us to bring the inputs to a certain range of values, which helps to improve the stability and speed of training convergence. more...
We will try to cover the most popular points about these previous topics to well understand what we need to deal with as programmers or developers. more...
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